You are given a directed graph of n nodes numbered from 0 to n - 1, where each node has at most one outgoing edge.
The graph is represented with a given 0-indexed array edges of size n, indicating that there is a directed edge from node i to node edges[i]. If there is no outgoing edge from i, then edges[i] == -1.
You are also given two integers node1 and node2.
Return the index of the node that can be reached from both node1 and node2, such that the maximum between the distance from node1 to that node, and from node2 to that node is minimized. If there are multiple answers, return the node with the smallest index, and if no possible answer exists, return -1.
Note that edges may contain cycles.
\n
Example 1:
\n![\"\"](\"https://assets.leetcode.com/uploads/2022/06/07/graph4drawio-2.png\")
\n\nInput: edges = [2,2,3,-1], node1 = 0, node2 = 1\nOutput: 2\nExplanation: The distance from node 0 to node 2 is 1, and the distance from node 1 to node 2 is 1.\nThe maximum of those two distances is 1. It can be proven that we cannot get a node with a smaller maximum distance than 1, so we return node 2.\n\n\n
Example 2:
\n![\"\"](\"https://assets.leetcode.com/uploads/2022/06/07/graph4drawio-4.png\")
\n\nInput: edges = [1,2,-1], node1 = 0, node2 = 2\nOutput: 2\nExplanation: The distance from node 0 to node 2 is 2, and the distance from node 2 to itself is 0.\nThe maximum of those two distances is 2. It can be proven that we cannot get a node with a smaller maximum distance than 2, so we return node 2.\n\n\n
\n
Constraints:
\n\nn == edges.length2 <= n <= 105-1 <= edges[i] < nedges[i] != i0 <= node1, node2 < nCompiled with clang 11 using the latest C++ 20 standard.
Your code is compiled with level two optimization (-O2). AddressSanitizer is also enabled to help detect out-of-bounds and use-after-free bugs.
Most standard library headers are already included automatically for your convenience.
\"], \"java\": [\"Java\", \"OpenJDK 17. Java 8 features such as lambda expressions and stream API can be used.
Most standard library headers are already included automatically for your convenience.
\\r\\nIncludes Pair class from https://docs.oracle.com/javase/8/javafx/api/javafx/util/Pair.html.
Python 2.7.12.
Most libraries are already imported automatically for your convenience, such as array, bisect, collections. If you need more libraries, you can import it yourself.
\\r\\n\\r\\nFor Map/TreeMap data structure, you may use sortedcontainers library.
\\r\\n\\r\\nNote that Python 2.7 will not be maintained past 2020. For the latest Python, please choose Python3 instead.
\"], \"c\": [\"C\", \"Compiled with gcc 8.2 using the gnu11 standard.
Your code is compiled with level one optimization (-O1). AddressSanitizer is also enabled to help detect out-of-bounds and use-after-free bugs.
Most standard library headers are already included automatically for your convenience.
\\r\\n\\r\\nFor hash table operations, you may use uthash. \\\"uthash.h\\\" is included by default. Below are some examples:
\\r\\n\\r\\n1. Adding an item to a hash.\\r\\n
\\r\\nstruct hash_entry {\\r\\n int id; /* we'll use this field as the key */\\r\\n char name[10];\\r\\n UT_hash_handle hh; /* makes this structure hashable */\\r\\n};\\r\\n\\r\\nstruct hash_entry *users = NULL;\\r\\n\\r\\nvoid add_user(struct hash_entry *s) {\\r\\n HASH_ADD_INT(users, id, s);\\r\\n}\\r\\n\\r\\n\\r\\n\\r\\n2. Looking up an item in a hash:\\r\\n
\\r\\nstruct hash_entry *find_user(int user_id) {\\r\\n struct hash_entry *s;\\r\\n HASH_FIND_INT(users, &user_id, s);\\r\\n return s;\\r\\n}\\r\\n\\r\\n\\r\\n\\r\\n3. Deleting an item in a hash:\\r\\n
\\r\\nvoid delete_user(struct hash_entry *user) {\\r\\n HASH_DEL(users, user); \\r\\n}\\r\\n\\r\\n\"], \"csharp\": [\"C#\", \"\"], \"javascript\": [\"JavaScript\", \"Node.js 16.13.2.
Your code is run with --harmony flag, enabling new ES6 features.
lodash.js library is included by default.
\\r\\n\\r\\nFor Priority Queue / Queue data structures, you may use 5.3.0 version of datastructures-js/priority-queue and 4.2.1 version of datastructures-js/queue.
\"], \"ruby\": [\"Ruby\", \"Ruby 3.1
Some common data structure implementations are provided in the Algorithms module: https://www.rubydoc.info/github/kanwei/algorithms/Algorithms
\"], \"swift\": [\"Swift\", \"Swift 5.5.2.
Go 1.21
Support https://godoc.org/github.com/emirpasic/gods@v1.18.1 library.
\"], \"python3\": [\"Python3\", \"Python 3.10.
Most libraries are already imported automatically for your convenience, such as array, bisect, collections. If you need more libraries, you can import it yourself.
\\r\\n\\r\\nFor Map/TreeMap data structure, you may use sortedcontainers library.
\"], \"scala\": [\"Scala\", \"Scala 2.13.7.
Kotlin 1.9.0.
Rust 1.58.1
Supports rand v0.6\\u00a0from crates.io
\"], \"php\": [\"PHP\", \"PHP 8.1.
With bcmath module
\"], \"typescript\": [\"Typescript\", \"TypeScript 5.1.6, Node.js 16.13.2.
Your code is run with --harmony flag, enabling new ES2022 features.
lodash.js library is included by default.
\"], \"racket\": [\"Racket\", \"Run with Racket 8.3.
Dart 2.17.3
\\r\\n\\r\\nYour code will be run directly without compiling
\"]}", "libraryUrl": null, "adminUrl": null, "challengeQuestion": { "id": "1209", "date": "2023-01-25", "incompleteChallengeCount": 0, "streakCount": 0, "type": "DAILY", "__typename": "ChallengeQuestionNode" }, "__typename": "QuestionNode" } } }